Rhoda AI
Research Member of Technical Staff- Efficient Modeling
Mountain View · Staff+
Sponsorship not specifiedDetected 64 days ago
Machine LearningDeep LearningPyTorchNLPRoboticsHardware DesignResearch
About the role
- We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.
- This work is critical to closing the gap between research-scale models and real-time operation on robot hardware.
Responsibilities
- Research and implement model compression techniques: quantization, pruning, structured sparsity, distillation, and low-rank approximation
- Design efficient architectures and attention mechanisms suited to real-time inference on edge and robot hardware
- Develop training strategies that produce better accuracy-efficiency tradeoffs from the start
- Build evaluation frameworks that measure capability retention after compression or architecture changes
- Collaborate with training systems and deployment teams to ensure efficient models translate to faster real-world inference
- We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots.
- Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design.
Requirements
- Strong understanding of model compression and efficient architectures for large models
- Hands-on experience with quantization, distillation, or pruning applied to transformers or large neural networks
- Deep knowledge of where efficiency gains are possible in modern architectures
- Proficiency with PyTorch and familiarity with hardware-aware optimization (CUDA, TensorRT, or similar)
- Ability to run principled experiments that characterize capability-efficiency tradeoffs
- PhD in ML, CS, or a related field - or equivalent research/engineering experience
- Experience with efficient video or multimodal model architectures
- Familiarity with edge deployment targets (Jetson, custom ASICs, or mobile hardware)
- Experience deploying compressed models on physical robots or latency-constrained systems
Nice to have
- Nice to Have (But Not Required)
Skills
- Profile and benchmark models across hardware targets to identify and resolve efficiency bottlenecks
- Publish and present work at top-tier venues
Company info
- What We're Looking For
- At Rhoda AI, we're building the next generation of generalist intelligent robots.
- We're looking for a Research Scientist or Research Engineer focused on model efficiency - making our foundation world models faster, smaller, and more deployable without sacrificing capability.
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